Speaker identification systems have been developed for years, and efforts continue to be made at improving upon prior versions. Several publications which provide but a small representation of the current state of the art include: D. A. Reynolds, “Experimental Evaluation of Features for Robust Speaker Identification”, IEEE Transactions on Speech and Audio Processing, Vol. 2, No. 4, pp. 639–643, 1994; D. A. Reynolds and R. C. Rose, “Robust Text-Independent Speaker Identification Using Gaussian Mixture Speaker Models”, IEEE Transactions on Speech and Audio Processing, Vol. 3, No. 1, pp. 72–83, January 1995; and U. V. Chaudhari, J. Navratil, S. H. Maes, and Ramesh Gopinath “Transformation Enhanced Multi-Grained Modeling for Text-Independent Speaker Recognition”, ICSLP 2000, pp. II.298–II.301.
Among the disadvantages observed in connection with conventional speaker identification systems is that such systems are generally not configured for being able to determine when a system result is inconclusive. Accordingly, a need has been recognized in connection with overcoming such disadvantages.